Losing sleep influences dietary intake in children: a longitudinal compositional analysis of a randomised crossover trial.

BACKGROUND: Although inadequate sleep increases the risk of obesity in children, the mechanisms remain unclear. The aims of this study were to assess how sleep loss influenced dietary intake in children while accounting for corresponding changes in sedentary time and physical activity; and to investigate how changes in time use related to dietary intake. METHODS: A randomized crossover trial in 105 healthy children (8-12 years) with normal sleep (~ 8-11 h/night) compared sleep extension (asked to turn lights off one hour earlier than usual for one week) and sleep restriction (turn lights off one hour later) conditions, separated by a washout week. 24-h time-use behaviors (sleep, wake after sleep onset, physical activity, sedentary time) were assessed using waist-worn actigraphy and dietary intake using two multiple-pass diet recalls during each intervention week. Longitudinal compositional analysis was undertaken with mixed effects regression models using isometric log ratios of time use variables as exposures and dietary variables as outcomes, and participant as a random effect. RESULTS: Eighty three children (10.2 years, 53% female, 62% healthy weight) had 47.9 (SD 30.1) minutes less sleep during the restriction week but were also awake for 8.5 (21.4) minutes less at night. They spent this extra time awake in the day being more sedentary (+ 31 min) and more active (+ 21 min light physical activity, + 4 min MVPA). After adjusting for all changes in 24-h time use, losing 48 min of sleep was associated with consuming significantly more energy (262 kJ, 95% CI:55,470), all of which was from non-core foods (314 kJ; 43, 638). Increases in sedentary time were related to increased energy intake from non-core foods (177 kJ; 25, 329) whereas increases in MVPA were associated with higher intake from core foods (72 kJ; 7,136). Changes in diet were greater in female participants. CONCLUSION: Loss of sleep was associated with increased energy intake, especially of non-core foods, independent of changes in sedentary time and physical activity. Interventions focusing on improving sleep may be beneficial for improving dietary intake and weight status in children. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ANZCTR ACTRN12618001671257, Registered 10th Oct 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367587&isReview=true.

Results from Aotearoa New Zealand's 2022 Report Card on Physical Activity for Children and Youth: A call to address inequities in health-promoting activities.

Background: This article reports the methods and findings for Aotearoa New Zealand's 2022 Report Card on Physical Activity for Children and Youth indicators, and on inequities within these indicators. Methods: Grades were assigned to indicators using the Active Healthy Kids Global Alliance criteria depending on data availability, and inequities reported based on gender, ethnicity, disability status, area-level socioeconomic deprivation, urbanicity, and school year. Two additional indicators were included in this report card: Sleep, and Physical literacy. Results: Grades were assigned to indicators as follows: Overall physical activity: C+, Organised sport and physical activity: B-, Physical literacy: B, Active transportation: D, Sedentary behaviours: C-, Sleep: B+, Whanau (family) and peers: D, School: C+, Government: A. Inequities across all socio-demographic variables were observed. An 'inconclusive' grade was assigned to the Active play, Physical fitness, and Community and Environment indicators due to insufficient data. Conclusion: It is imperative that targeted, comprehensive, and population-specific approaches are implemented to support health-promoting physical activity behaviours and reduce inequities among children and youth in Aotearoa. There is a need to promote all dimensions of physical activity (overall activity, active play, recreation, organised sport, active transportation) and the reduction of screen time through policy, research, evidence-based social marketing campaigns, and urban design. Regular, nationally representative surveys that enable the consistent and regular measurement of key Report Card indicators are needed.

Age- and sex-specific visceral fat reference cutoffs and their association with cardio-metabolic risk.

BACKGROUND: Although excess visceral fat (VAT) is associated with numerous cardio-metabolic risk factors, measurement of this fat depot has historically been difficult. Recent dual X-ray absorptiometry approaches have provided an accessible estimate of VAT that has shown acceptable validity against gold standard methods. The aims of this study were to (i) evaluate DXA measured VAT as a predictor of elevated blood lipids and blood pressure and (ii) calculate thresholds associated with these cardio-metabolic risk factors. SUBJECTS/METHODS: The sample comprised 1482 adults (56.4% women) aged 18-66 years. Total body scans were performed using a GE Lunar Prodigy, and VAT analyses were enabled through Corescan software (v 16.0). Blood pressure and blood lipids were measured by standard procedures. Regression models assessed how VAT mass was associated with each cardio-metabolic risk factor compared to other body composition measures. Measures of sensitivity and specificity were used to determine age- and sex-specific cut points for VAT mass associated with high cardio-metabolic risk. RESULTS: Similar to waist circumference, VAT mass was a strong predictor of cardio-metabolic risk especially in men over age 40. Four cut-offs for VAT mass were proposed, above which the cardio-metabolic risk increased: 700 g in women <40 yrs; 800 g in women 40+ yrs; 1000g in men <40 yrs; and 1200 g in men 40+ yrs. In general, these cut-offs discriminated well between those with high and low cardio-metabolic risk. CONCLUSIONS: In both sexes, DXA measured VAT was associated with traditional cardio-metabolic risk factors, particularly high blood pressure in those 40+ yrs and low HDL < 40 yrs. These reference values provide a simple, accessible method to assess cardio-metabolic risk in adults.

Adherence to 24-h movement behavior guidelines and psychosocial functioning in young children: a longitudinal analysis.

BACKGROUND: A recent paradigm shift has highlighted the importance of considering how sleep, physical activity and sedentary behaviour work together to influence health, rather than examining each behaviour individually. We aimed to determine how adherence to 24-h movement behavior guidelines from infancy to the preschool years influences mental health and self-regulation at 5 years of age. METHODS: Twenty-four hour movement behaviors were measured by 7-day actigraphy (physical activity, sleep) or questionnaires (screen time) in 528 children at 1, 2, 3.5, and 5 years of age and compared to mental health (anxiety, depression), adaptive skills (resilience), self-regulation (attentional problems, hyperactivity, emotional self-control, executive functioning), and inhibitory control (Statue, Head-Toes-Knees-Shoulders task) outcomes at 5 years of age. Adjusted standardised mean differences (95% CI) were determined between those who did and did not achieve guidelines at each age. RESULTS: Children who met physical activity guidelines at 1 year of age (38.7%) had lower depression (mean difference [MD]: -0.28; 95% CI: -0.51, -0.06) and anxiety (MD: -0.23; 95% CI: -0.47, 0.00) scores than those who did not. At the same age, sleeping for 11-14 h or having consistent wake and sleep times was associated with lower anxiety (MD: -0.34; 95% CI: -0.66, -0.02) and higher resilience (MD: 0.35; 95% CI: 0.03, 0.68) scores respectively. No significant relationships were observed at any other age or for any measure of self-regulation. Children who consistently met screen time guidelines had lower anxiety (MD: -0.43; 95% CI: -0.68, -0.18) and depression (MD: -0.36; 95% CI: -0.62, -0.09) scores at 5. However, few significant relationships were observed for adherence to all three guidelines; anxiety scores were lower (MD: -0.42; 95% CI: -0.72, -0.12) in the 20.2% who adhered at 1 year of age, and depression scores were lower (MD: -0.25; 95% CI: -0.48, -0.02) in the 36.7% who adhered at 5 years of age compared with children who did not meet all three guidelines. CONCLUSIONS: Although adherence to some individual movement guidelines at certain ages throughout early childhood was associated with improved mental health and wellbeing at 5 years of age, particularly reduced anxiety and depression scores, there was little consistency in these relationships. Future work should consider a compositional approach to 24-h time use and how it may influence mental wellbeing. TRIAL REGISTRATION: ClinicalTrials.gov number NCT00892983.

Measuring short-term eating behaviour and desire to eat: Validation of the child eating behaviour questionnaire and a computerized 'desire to eat' computerized questionnaire.

The Child Eating Behaviour Questionnaire (CEBQ) is designed to measure 'usual' eating behaviour, with no time period attached, thus may not be suitable for assessing the effectiveness of short-term experimental studies. The aim of this study was to validate i) the CEBQ adapted to measure 'past week' rather than 'usual' eating behaviour, and ii) a computerized questionnaire assessing desire to eat core and non-core foods, against an objective measure of eating behaviour and food intake (eating in the absence of hunger (EAH) experiment). Children (n = 103) aged 8-12 years completed the desire to eat questionnaire followed by the EAH experiment while primary caregivers completed the adapted CEBQ. Results from the CEBQ showed that children with greater 'satiety responsiveness' (1-point higher) consumed less energy (-342 kJ; 95% CI -574, -110) whereas those with greater 'enjoyment of food' scale consumed more energy (380 kJ; 95% CI 124, 636) during the ad-libitum phase of the EAH experiment. Higher scores for slowness in eating (-705 kJ; 95% CI -1157, -254), emotional undereating (-590 kJ; 95% CI -1074, -106) and food fussiness (-629 kJ; 95% CI -1103, -155) were associated with lower total energy intake. Children who expressed greater desire to eat non-core foods consumed more energy in total (275 kJ; 95% CI 87, 463). Overall, this adapted CEBQ appears valid for measuring several short-term eating behaviours in children. The desire to eat questionnaire may be useful for identifying short-term susceptibility to overeating, however further investigation into how ratings of desire relate to the intake of highly palatable, energy dense foods is warranted.

Quantity versus quality of objectively measured sleep in relation to body mass index in children: cross-sectional and longitudinal analyses.

BACKGROUND/OBJECTIVES: Although sleep duration is well established as a risk factor for child obesity, how measures of sleep quality relate to body size is less certain. The aim of this study was to determine how objectively measured sleep duration, sleep timing, and sleep quality were related to body mass index (BMI) cross-sectionally and longitudinally in school-aged children. SUBJECTS/METHODS: All measures were obtained at baseline, 12 and 24 months in 823 children (51% female, 53% European, 18% Maori, 12% Pacific, 9% Asian) aged 6-10 years at baseline. Sleep duration, timing, and quality were measured using actigraphy over 7 days, height and weight were measured using standard techniques, and parents completed questionnaires on demographics (baseline only), dietary intake, and television usage. Data were analysed using imputation; mixed models, with random effects for person and age, estimated both a cross-sectional effect and a longitudinal effect on BMI z-score, adjusted for multiple confounders. RESULTS: The estimate of the effect on BMI z-score for each additional hour of sleep was -0.22 (95% CI: -0.33, -0.11) in cross-sectional analyses and -0.05 (-0.10, -0.004) in longitudinal analyses. A greater effect was observed for weekday sleep duration than weekend sleep duration but variability in duration was not related to BMI z-score. While sleep timing (onset or midpoint of sleep) was not related to BMI, children who were awake in the night more frequently (0.19; 0.06, 0.32) or for longer periods (0.18; 0.06, 0.36) had significantly higher BMI z-scores cross-sectionally, but only the estimates for total time awake (minutes) were significant longitudinally (increase in BMI z-score of 0.04 for each additional hour awake). CONCLUSION: The beneficial effect of a longer sleep duration on BMI was consistent in children, whereas evidence for markers of sleep quality and timing were more variable.

Do young children consistently meet 24-h sleep and activity guidelines? A longitudinal analysis using actigraphy.

BACKGROUND: Existing studies examining adherence to 24-h movement guidelines in young children are mostly cross sectional and have not assessed additional guidelines relating to activity intensity or regularity in sleep patterns. The aims of this study were to determine adherence to full sleep, activity, and sedentary behaviour guidelines from 1-5 years of age, whether adherence tracked over time, and how adherence was related to body composition cross sectionally and prospectively. SUBJECTS/METHODS: Data were obtained from 547 children who were participants in a randomised controlled trial. At 1, 2, and 5 years of age, children wore Actical accelerometers 24-h a day for 5-7 days, height and weight were measured, and parents completed questionnaires on screen time and restraint (1 and 2 years only). A dual-energy x-ray absorptiometry (DXA) scan measured body composition at 5 years of age. RESULTS: Although adherence to general sleep and activity guidelines was high, few children had regular sleep patterns. Adherence to all three guidelines ranged from 12.3 to 41.3% at the different ages, although these estimates decreased to 0.6-9.3% when activity intensity (60 min of energetic play) and sleep regularity (consistent sleep and wake times) were included. Children who met all three guidelines at a given age were more likely to meet all three guidelines at a subsequent age (odds ratio, 95% CI: 2.6, 1.04-6.4 at 1 year and 2.5, 1.1-5.9 at 2 years). However, adherence to meeting all three guidelines at earlier ages was not related to BMI z-score or body composition at age 5, either cross sectionally or prospectively. CONCLUSIONS: Strategies to promote adherence to movement guidelines among young children are warranted, particularly to reduce screen time, and encouraging regular sleep patterns.

Efficacy of a compulsory homework programme for increasing physical activity and improving nutrition in children: a cluster randomised controlled trial.

BACKGROUND: Most physical activity interventions in children focus on the school setting; however, children typically engage in more sedentary activities and spend more time eating when at home. The primary aim of this cluster randomised controlled trial was to investigate the effects of a compulsory, health-related homework programme on physical activity, dietary patterns, and body size in primary school-aged children. METHODS: A total of 675 children aged 7-10 years from 16 New Zealand primary schools participated in the Healthy Homework study. Schools were randomised into intervention and control groups (1:1 allocation). Intervention schools implemented an 8-week applied homework and in-class teaching module designed to increase physical activity and improve dietary patterns. Physical activity was the primary outcome measure, and was assessed using two sealed pedometers that monitored school- and home-based activity separately. Secondary outcome measures included screen-based sedentary time and selected dietary patterns assessed via parental proxy questionnaire. In addition, height, weight, and waist circumference were measured to obtain body mass index (BMI) and waist-to-height ratio (WHtR). All measurements were taken at baseline (T0), immediately post-intervention (T1), and 6-months post-intervention (T2). Changes in outcome measures over time were estimated using generalised linear mixed models (GLMMs) that adjusted for fixed (group, age, sex, group x time) and random (subjects nested within schools) effects. Intervention effects were also quantified using GLMMs adjusted for baseline values. RESULTS: Significant intervention effects were observed for weekday physical activity at home (T1 [P < 0.001] and T2 [P = 0.019]), weekend physical activity (T1 [P < 0.001] and T2 [P < 0.001]), BMI (T2 only [P = 0.020]) and fruit consumption (T1 only [P = 0.036]). Additional analyses revealed that the greatest improvements in physical activity occurred in children from the most socioeconomically deprived schools. No consistent effects on sedentary time, WHtR, or other dietary patterns were observed. CONCLUSIONS: A compulsory health-related homework programme resulted in substantial and consistent increases in children's physical activity - particularly outside of school and on weekends - with limited effects on body size and fruit consumption. Overall, our findings support the integration of compulsory home-focused strategies for improving health behaviours into primary education curricula. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12618000590268 . Registered 17 April 2018.

The effect of mild sleep deprivation on diet and eating behaviour in children: protocol for the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized cross-over trial.

BACKGROUND: Although insufficient sleep has emerged as a strong, independent risk factor for obesity in children, the mechanisms by which insufficient sleep leads to weight gain are uncertain. Observational research suggests that being tired influences what children eat more than how active they are, but only experimental research can determine causality. Few experimental studies have been undertaken to determine how reductions in sleep duration might affect indices of energy balance in children including food choice, appetite regulation, and sedentary time. The primary aim of this study is to objectively determine whether mild sleep deprivation increases energy intake in the absence of hunger. METHODS: The Daily, Rest, Eating, and Activity Monitoring (DREAM) study is a randomized controlled trial investigating how mild sleep deprivation influences eating behaviour and activity patterns in children using a counterbalanced, cross-over design. One hundred and ten children aged 8-12 years, with normal reported sleep duration of 8-11 h per night will undergo 2 weeks of sleep manipulation; seven nights of sleep restriction by going to bed 1 hr later than usual, and seven nights of sleep extension going to bed 1 hr earlier than usual, separated by a washout week. During each experimental week, 24-h movement behaviours (sleep, physical activity, sedentary behaviour) will be measured via actigraphy; dietary intake and context of eating by multiple 24-h recalls and wearable camera images; and eating behaviours via objective and subjective methods. At the end of each experimental week a feeding experiment will determine energy intake from eating in the absence of hunger. Differences between sleep conditions will be determined to estimate the effects of reducing sleep duration by 1-2 h per night. DISCUSSION: Determining how insufficient sleep predisposes children to weight gain should provide much-needed information for improving interventions for the effective prevention of obesity, thereby decreasing long-term morbidity and healthcare burden. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12618001671257 . Registered 10 October 2018.

Physical activity and inactivity trajectories associated with body composition in pre-schoolers.

BACKGROUND/OBJECTIVES: Early childhood is characterised by rapid development and is a critical period for the establishment of activity behaviours. We aim to examine how physical activity (PA) and sedentary behaviour (SB) track during the first 5 years of life, and to investigate associations between trajectories and body composition at 5 years of age. SUBJECTS/METHODS: A total of 438 participants (50% male) wore an Actical accelerometer for 5 days at at least two of 1, 2, 3.5 and 5 years of age. Spearman correlation coefficients examined PA tracking from age 1 to 5 and trajectories of PA and SB were estimated using discrete mixture modelling. Regression models tested associations between both PA and SB trajectories and body composition measures. RESULTS: Tracking coefficients for PA ranged from r = 0.31-0.51 across the ages, with similar tracking observed for sedentary behaviour (r = 0.21-0.39). Four distinct trajectory patterns were identified separately for PA and SB: consistently low, consistently high, increasing and decreasing. BMI and waist circumference were not significantly associated with PA trajectories, but those in the consistently high activity group had significantly lower % body fat (95% CI) at age 5 (14.3%; 13.5, 15.2) than those in the consistently low (16.8%; 15.6, 18.2) or increasing (15.7%; 14.7, 16.7) groups (P = 0.017). Sedentary behaviour trajectories were not associated with any of the anthropometric measures at age 5 (P > 0.05). CONCLUSIONS: Physical activity and sedentary behaviour tracking is broadly similar from infancy to early childhood. Children with consistently higher levels of physical activity have reduced body fat at 5 years of age, although differences are relatively small.

Sleep timing is associated with diet and physical activity levels in 9-11-year-old children from Dunedin, New Zealand: the PEDALS study.

It is well documented that short sleep duration is associated with excess body weight and poor food intake in children. It has been suggested that sleep timing behaviour may also be an important predictor of weight and other related behaviours, independent of sleep duration; however, there is a lack of research investigating these relationships. The present study investigated sleep timing in association with diet and physical activity levels in 439 children aged 9-11 years old from New Zealand. Sleep and physical activity data were collected using accelerometry, and food choice using a short food-frequency questionnaire. Participants were classified into one of four sleep timing behaviour categories using the median split for sleep-onset and -offset times. Differences between sleep timing groups for weekly consumption frequency of selected food groups, dietary pattern scores and minutes of moderate-to-vigorous physical activity were examined. Children in the late sleep/late wake category had a lower 'Fruit & Vegetables' pattern score [mean difference (95% CI): -0.3 (-0.5, -0.1)], a lower consumption frequency of fruit and vegetables [mean weekly difference (95% CI): -2.9 (-4.9, -0.9)] and a higher consumption frequency of sweetened beverages [mean weekly difference (95% CI): 1.8 (0.2, 3.3)] compared with those in the early sleep/early wake category. Additionally, children in the late sleep/late wake category accumulated fewer minutes of moderate-to-vigorous physical activity per day compared with those in the early sleep/early wake category [mean difference (95% CI): -9.4 (-15.3, -3.5)]. These findings indicate that sleep timing, even after controlling for sleep duration, was associated with both food consumption and physical activity.

24-h movement behaviors from infancy to preschool: cross-sectional and longitudinal relationships with body composition and bone health.

BACKGROUND: New physical activity guidelines for children address all movement behaviors across the 24-h day (physical activity, sedentary behavior, sleep), but how each component relates to body composition when adjusted for the compositional nature of 24-h data is uncertain. AIMS: To i) describe 24-h movement behaviors from 1 to 5 years of age, ii) determine cross-sectional relationships with body mass index (BMI) z-score, iii) determine whether movement behaviors from 1 to 5 years of age predict body composition and bone health at 5 years. METHODS: 24-h accelerometry data were collected in 380 children over 5-7 days at 1, 2, 3.5 and 5 years of age to determine the proportion of the day spent: sedentary (including wake after sleep onset), in light (LPA) and moderate-to-vigorous physical activity (MVPA), and asleep (including naps). BMI was determined at each age and a dual-energy x-ray absorptiometry (DXA) scan measured fat mass, bone mineral content (BMC) and bone mineral density (BMD) at 5 years of age. 24-h movement data were transformed into isometric log-ratio co-ordinates for multivariable regression analysis and effect sizes back-transformed. RESULTS: At age 1, children spent 49.6% of the 24-h day asleep, 38.2% sedentary, 12.1% in LPA, and 0.1% in MVPA, with corresponding figures of 44.4, 33.8, 19.8 and 1.9% at 5 years of age. Compositional time use was only related significantly to BMI z-score at 3.5 years in cross-sectional analyses. A 10% increase in mean sleep time (65 min) was associated with a lower BMI z-score (estimated difference, - 0.25; 95% CI, - 0.42 to - 0.08), whereas greater time spent sedentary (10%, 47 min) or in LPA (10%, 29 min) were associated with higher BMI z-scores (0.12 and 0.08 respectively, both p < 0.05). Compositional time use from 1 to 3.5 years was not related to future BMI z-score or percent fat. Although MVPA at 2 and 3.5 years was consistently associated with higher BMD and BMC at 5 years, actual differences were small. CONCLUSIONS: Considerable changes in compositional time use occur from 1 to 5 years of age, but there is little association with adiposity. Although early MVPA predicted better bone health, the differences observed had little clinical relevance. TRIAL REGISTRATION: ClinicalTrials.gov number NCT00892983 .

Three-year follow-up of a randomised controlled trial to reduce excessive weight gain in the first two years of life: protocol for the POI follow-up study.

BACKGROUND: The Prevention of Overweight in Infancy (POI) study was a four-arm randomised controlled trial (RCT) in 802 families which assessed whether additional education and support on sleep (Sleep group); food, physical activity and breastfeeding (FAB group); or both (Combination group), reduced excessive weight gain from birth to 2 years of age, compared to usual care (Control group). The study had high uptake at recruitment (58 %) and retention at 2 years (86 %). Although the FAB intervention produced no significant effect on BMI or weight status at 2 years, the odds of obesity were halved in those who received the sleep intervention, despite no apparent effect on sleep duration. We speculate that enhanced self-regulatory behaviours may exist in the Sleep group. Self-regulation was not measured in our initial intervention, but extensive measures have been included in this follow-up study. Thus, the overall aim of the POI follow-up is to determine the extent to which augmented parental support and education on infant sleep, feeding, diet, and physical activity in the first 2 years of life reduces BMI at 3.5 and 5 years of age, and to determine the role of self-regulation in any such relationship. METHODS/DESIGN: We will contact all 802 families and seek renewed consent to participate in the follow-up study. The families have received no POI intervention since the RCT finished at 2 years of age. Follow-up data collection will occur when the children are aged 3.5 and 5 years (i.e. up to 3 years post-intervention). Outcomes of interest include child anthropometry, body composition (DXA scan), diet (validated food frequency questionnaire), physical activity (accelerometry), sleep (questionnaire and accelerometry), and self-regulation (questionnaires and neuropsychological assessment). DISCUSSION: Our follow-up study has been designed primarily to enable us to determine whether the intriguing benefit of the sleep intervention suggested at 2 years of age remains as children approach school age. However, cohort analyses will also investigate how BMI, self-regulation, and sleep consolidation develop during the early years. This information will be valuable to researchers and policy makers progressing the field of early childhood obesity prevention. TRIAL REGISTRATION: ClinicalTrials.gov number NCT00892983 .

24 h Accelerometry: impact of sleep-screening methods on estimates of sedentary behaviour and physical activity while awake.

Although accelerometers can assess sleep and activity over 24 h, sleep data must be removed before physical activity and sedentary time can be examined appropriately. We compared the effect of 6 different sleep-scoring rules on physical activity and sedentary time. Activity and sleep were obtained by accelerometry (ActiGraph GT3X) over 7 days in 291 children (51.3% overweight or obese) aged 4-8.9 years. Three methods removed sleep using individualised time filters and two methods applied standard time filters to remove sleep each day (9 pm-6 am, 12 am-6 am). The final method did not remove sleep but simply defined non-wear as at least 60 min of consecutive zeros over the 24-h period. Different methods of removing sleep from 24-h data markedly affect estimates of sedentary time, yielding values ranging from 556 to 1145 min/day. Estimates of non-wear time (33-193 min), wear time (736-1337 min) and counts per minute (384-658) also showed considerable variation. By contrast, estimates of moderate-to-vigorous activity (MVPA) were similar, varying by less than 1 min/day. Different scoring methods to remove sleep from 24-h accelerometry data do not affect measures of MVPA, whereas estimates of counts per minute and sedentary time depend considerably on which technique is used.

Determining how best to support overweight adults to adhere to lifestyle change: protocol for the SWIFT study.

BACKGROUND: Physical activity plays a critical role in health, including for effective weight maintenance, but adherence to guidelines is often poor. Similarly, although debate continues over whether a "best" diet exists for weight control, meta-analyses suggest little difference in outcomes between diets differing markedly in macronutrient composition, particularly over the longer-term. Thus a more important question is how best to encourage adherence to appropriate lifestyle change. While brief support is effective, it has on-going cost implications. While self-monitoring (weight, diet, physical activity) is a cornerstone of effective weight management, little formal evaluation of the role that self-monitoring technology can play in enhancing adherence to change has occurred to date. People who eat in response to hunger have improved weight control, yet how best to train individuals to recognise when true physical hunger occurs and to limit consumption to those times, requires further study. METHODS/DESIGN: SWIFT (Support strategies for Whole-food diets, Intermittent Fasting, and Training) is a two-year randomised controlled trial in 250 overweight (body mass index of 27 or greater) adults that will examine different ways of supporting people to make appropriate changes to diet and exercise habits for long-term weight control. Participants will be randomised to one of five intervention groups: control, brief support (monthly weigh-ins and meeting), app (use of MyFitnessPal with limited support), daily self-weighing (with brief monthly feedback), or hunger training (four-week programme which trains individuals to only eat when physically hungry) for 24 months. Outcome assessments include weight, waist circumference, body composition (dual-energy x-ray absorptiometry), inflammatory markers, blood lipids, adiponectin and ghrelin, blood pressure, diet (3-day diet records), physical activity (accelerometry) and aerobic fitness, and eating behaviour. SWIFT is powered to detect clinically important differences of 4 kg in body weight and 5 cm in waist circumference. Our pragmatic trial also allows participants to choose one of several dietary (Mediterranean, modified Paleo, intermittent fasting) and exercise (current recommendations, high-intensity interval training) approaches before being randomised to a support strategy. DISCUSSION: SWIFT will compare four different ways of supporting overweight adults to lose weight while following a diet and exercise plan of their choice, an aspect we believe will enhance adherence and thus success with weight management. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12615000010594. Registered 8th January 2015.

Using motivational interviewing for weight feedback to parents of young children.

AIM: To determine whether a single session of motivational interviewing (MI) for feedback of a child's overweight status promotes engagement in treatment following screening. METHODS: One thousand ninety-three children aged 4-8 years were recruited through primary and secondary care to attend health screening, including assessment of parenting practices and motivation (questionnaire). Families with normal-weight children were informed about their child's weight but had no further involvement. Parents of overweight (body mass index ≥ 85th percentile) children (n = 271) were randomised to receive weight feedback via MI or best practice care (BPC) using a traffic light concept to indicate degree of health risk. Follow-up interviews were held 2 weeks later to examine intervention uptake, changes to motivation and behaviour, and parental response to feedback. RESULTS: Recruitment into the intervention was high (76%) and not altered by feedback condition (percentage difference 6.6 (95% confidence interval -2.9, 16.0). High scores on the Health Care Climate Questionnaire (rating of the interviewer) indicated satisfaction with how the information was provided to parents. No differences were observed in multiple indicators of harm. However, self-determined motivation for healthy life-styles was significantly higher in the MI condition at follow-up (0.18: 0.00, 0.35), after only a single session of MI. CONCLUSIONS: MI and BPC were both successful in encouraging parents to participate in a family-based intervention, with MI offering little significant benefit over BPC. A traffic light approach to weight feedback is a suitable way of providing sensitive information to parents not expecting such news.

What factors influence uptake into family-based obesity treatment after weight screening?

OBJECTIVES: To determine what factors drive participation in a family-based weight management program for 4- to 8-year-old children following screening for overweight or obesity. STUDY DESIGN: Children (n = 1093) attended a comprehensive screening appointment where parents completed questionnaires on demographics, motivation for healthy lifestyles, feeding practices, and beliefs about child size, prior to feedback about the child's weight. Parents of overweight or obese children (body mass index ≥85th percentile) attended a follow-up interview to assess reactions to feedback and willingness to participate in a 2-year intervention. RESULTS: A total of 271 (24.8%) children were overweight or obese with 197 (72.7%) agreeing to the intervention. Socioeconomic status differed in intervention participants (n = 197) compared with non-participants (n = 74), whereas no differences were observed in parental feeding practices, ineffective parenting practices, or self-determined forms of motivation. However, fewer non-participating parents believed their child to be overweight (23% vs 49%, P < .001) or were concerned about it (16% vs 43%, P < .001), despite children having an average body mass index approximating the 95th percentile. Non-participating parents did not expect their child to be overweight (P = .002) and rated receiving this information as less useful (P = .008) than participating parents. CONCLUSION: Preconceptions about child weight and reactions to feedback determined intervention uptake more than parenting or motivation for health. Many parents agreed to participate in the intervention despite not viewing their child as overweight.

High-intensity interval aerobic and resistance training to counteract low relative lean soft tissue mass in middle age: A randomized controlled trial.

BACKGROUND: Age-related loss of skeletal muscle mass and function begins in early middle age, yet research to date has focused on older individuals, limiting our understanding of interventions earlier in the lifespan. To date, no high-intensity interval training studies have been conducted in middle-aged adults with low relative lean soft tissue mass. METHODS: Eighty-two middle-aged adults (40-50 years of age) with low appendicular lean soft tissue mass index confirmed with dual energy x-ray absorptiometry (DXA) were randomly allocated (1:1) to group-based, 20-week, three times a week, high-intensity aerobic and resistance training (HIART) program or 60-min education session (Control). The primary outcome was change in total lean soft tissue mass measured by DXA. Secondary outcomes included cardiorespiratory fitness, physical function (handgrip strength, gait speed, 30-seconds sit-to-stand, quadriceps strength and muscle quality). Measures were obtained at baseline (0 weeks), mid-intervention (10 weeks) and post-intervention (20 weeks). RESULTS: Mean age in HIART was 44.8 (SD 3.2) and 45.4 (SD 2.9) in Control group. The majority of the participants were female with 88 % in HIART and 83 % in Control group. Mean BMI in HIART was 25.8 kg/m2 (SD 3.5) and 26.4 kg/m2 (SD 4.1) Control group. Intention to treat analysis showed that post-intervention, HIART increased significantly more total lean soft tissue mass (0.8 kg, 95%CI 0.15, 1.46), appendicular lean soft tissue mass index (0.2 kg/m2, 95%CI 0.09, 0.33), peak oxygen uptake (5.18 mL/min/kg, 2.97 to 7.39 95%CI), grip strength (2.2 kg, 95%CI 0.09, 4.32), and 30-s sit-to-stand (1.3 times, 95%CI 0.43, 2.12) with significantly greater reductions in body fat percentage (-1.1 %, 95%CI -2.03, -0.10) and maximum gait speed (-0.2 m/s, 95 % CI -0.34, -0.03) compared Control. CONCLUSION: The HIART program is an effective exercise intervention to increase total lean soft tissue mass in middle-aged adults with low relative lean soft tissue mass compared to a waitlist control group.

Where does the time go when children don't sleep? A randomized crossover study.

OBJECTIVE: This study aimed to describe how mild sleep deprivation in children changes time spent physically active and sedentary. METHODS: In 2018 through 2020, children (n = 105) with normal sleep were randomized to go to bed 1 hour earlier (extension) or 1 hour later (restriction) than their usual bedtime for 1 week, each separated by a 1-week washout. Twenty-four-hour movement behaviors were measured with waist-worn actigraphy and expressed in minutes and proportions (percentages). Mixed-effects regression models determined mean differences in time use (95% CI) between conditions. Time gained from sleep lost that was reallocated to other movement behaviors in the 24-hour day was modeled using regression. RESULTS: Children (n = 96) gained ~49 minutes of awake time when sleep was restricted compared with extended. This time was mostly reallocated to sedentary behavior (28 minutes; 95% CI: 19-37), followed by physical activity (22 minutes; 95% CI: 14-30). When time was expressed as a percentage, the overall composition of movement behavior remained similar across both sleep conditions. CONCLUSIONS: Children were not less physically active when mildly sleep deprived. Time gained from sleeping less was proportionally, rather than preferentially, reallocated to sedentary time and physical activity. These findings suggest that decreased physical activity seems unlikely to explain the association between short sleep and obesity in children.

Effect of Sleep Changes on Health-Related Quality of Life in Healthy Children: A Secondary Analysis of the DREAM Crossover Trial.

Importance: Little is known regarding the effect of poor sleep on health-related quality of life (HRQOL) in healthy children. Objective: To determine the effect of induced mild sleep deprivation on HRQOL in children without major sleep issues. Design, Setting, and Participants: This prespecified secondary analysis focused on HRQOL, a secondary outcome of the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized crossover trial of children who underwent alternating weeks of sleep restriction and sleep extension and a 1-week washout in between. The DREAM trial intervention was administered at participants' homes between October 2018 and March 2020. Participants were 100 children aged 8 to 12 years who lived in Dunedin, New Zealand; had no underlying medical conditions; and had parent- or guardian-reported normal sleep (8-11 hours/night). Data were analyzed between July 4 and September 1, 2022. Interventions: Bedtimes were manipulated to be 1 hour later (sleep restriction) and 1 hour earlier (sleep extension) than usual for 1 week each. Wake times were unchanged. Main Outcomes and Measures: All outcome measures were assessed during both intervention weeks. Sleep timing and duration were assessed using 7-night actigraphy. Children and parents rated the child's sleep disturbances (night) and impairment (day) using the 8-item Pediatric Sleep Disturbance and 8-item Sleep-Related Impairment scales of the Patient-Reported Outcomes Measurement Information System questionnaire. Child-reported HRQOL was assessed using the 27-item KIDSCREEN questionnaire with 5 subscale scores and a total score. Both questionnaires assessed the past 7 days at the end of each intervention week. Data were presented as mean differences and 95% CIs between the sleep restriction and extension weeks and were analyzed using intention to treat and an a priori difference in sleep of at least 30 minutes per night. Results: The final sample comprised 100 children (52 girls [52%]; mean [SD] age, 10.3 [1.4] years). During the sleep restriction week, children went to sleep 64 (95% CI, 58-70) minutes later, and sleep offset (wake time) was 18 (95% CI, 13-24) minutes later, meaning that children received 39 (95% CI, 32-46) minutes less of total sleep per night compared with the sleep extension week in which the total sleep time was 71 (95% CI, 64-78) minutes less in the per-protocol sample analysis. Both parents and children reported significantly less sleep disturbance at night but greater sleep impairment during the day with sleep restriction. Significant standardized reductions in physical well-being (standardized mean difference [SMD], -0.28; 95% CI, -0.49 to -0.08), coping in a school environment (SMD, -0.26; 95% CI, -0.42 to -0.09), and total HRQOL score (SMD, -0.21; 95% CI, -0.34 to -0.08) were reported by children during sleep restriction, with an additional reduction in social and peer support (SMD, -0.24; 95% CI, -0.47 to -0.01) in the per-protocol sample analysis. Conclusions and Relevance: Results of this secondary analysis of the DREAM trial indicated that even 39 minutes less of sleep per night for 1 week significantly reduced several facets of HRQOL in children. This finding shows that ensuring children receive sufficient good-quality sleep is an important child health issue. Trial Registration: Australian New Zealand Clinical Trials Registry: ACTRN12618001671257.